Intelligent fire extinguishing method and system for foam fire truck, foam fire truck and storage medium

Abstract

The application provides a foam fire truck intelligent fire extinguishing method and system, a foam fire truck and a storage medium. The method comprises the following steps: acquiring fire scene information, wherein the fire scene information comprises a fire point, fire temperature distribution information and a first distance, the first distance being the distance between a fire gun and the fire point; determining the mixing ratio of the fire extinguishing medium of the foam fire truck according to the first distance, the mixing ratio of the fire extinguishing medium being the mixing ratio of foam and water; determining the volume of the fire-fighting foam required for extinguishing the fire according to the fire temperature distribution information; and driving the fire-fighting foam proportion mixing system of the foam fire truck to produce the fire-fighting foam according to the mixing ratio and the fire-fighting foam. The application can improve the selection accuracy of the mixing ratio of the fire extinguishing medium, improve the accurate judgment of the medium demand during fire extinguishing and rescue, save resources, improve the rescue speed and reduce economic losses.

Description

Technical Field

[0001] This application relates to the field of fire protection technology, and in particular to an intelligent fire extinguishing method, system, foam fire truck, and storage medium for foam fire trucks. Background Technology

[0002] With the gradual development of the fire protection industry, there are increasingly more types of foam liquids suitable for Class A and Class B fires. When used, the foam liquid is mixed with water in a specific ratio, and air is drawn in to form foam while it is being sprayed from a foam cannon or foam gun. This foam is then sprayed onto the surface of the burning material to form a covering layer, achieving the purpose of extinguishing the fire.

[0003] In existing fire-fighting foam proportioning systems deployed on fire trucks, the foam-to-water mixing ratio is typically selected based on the judgment of on-site firefighters to achieve fire extinguishing with foam of a suitable ratio. However, this method of judgment is highly subjective, which can lead to inaccurate assessment of the fire situation, affecting fire suppression efficiency, and inaccurate selection of the mixing ratio, impacting rescue speed and causing serious economic losses. Summary of the Invention

[0004] This application provides an intelligent fire extinguishing method, system, foam fire truck, and storage medium for foam fire trucks, in order to solve the problem of unintelligent selection of foam mixing ratio in existing technologies.

[0005] Firstly, this application provides an intelligent fire extinguishing method for foam fire trucks, including:

[0006] Acquire fire scene information, which includes the ignition point, fire temperature distribution information, and a first distance, wherein the first distance is the distance between the fire hose and the ignition point of the fire.

[0007] Based on the first distance, the mixing ratio of the extinguishing medium of the foam fire truck is determined, wherein the mixing ratio of the extinguishing medium is the mixing ratio of foam and water;

[0008] Based on the fire temperature distribution information, determine the volume of fire-fighting foam required to extinguish the fire;

[0009] The fire-fighting foam is produced by the fire-fighting foam proportioning system of the foam fire truck, based on the mixing ratio and the volume of the fire-fighting foam.

[0010] Secondly, this application provides an intelligent fire extinguishing system for foam fire trucks, comprising:

[0011] The acquisition module is used to acquire fire scene information, which includes the ignition point, fire temperature distribution information, and a first distance, wherein the first distance is the distance between the fire hose and the ignition point of the fire.

[0012] A mixing ratio determination module is used to determine the mixing ratio of the extinguishing medium of the foam fire truck based on the first distance, wherein the mixing ratio of the extinguishing medium is the mixing ratio of foam and water;

[0013] The volume determination module is used to determine the volume of fire-fighting foam required to extinguish the fire based on the fire temperature distribution information.

[0014] A drive module is used to drive the fire foam proportioning system of the foam fire truck to produce the fire foam according to the mixing ratio and the volume of the fire foam.

[0015] Thirdly, this application provides a foam fire truck, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of the method as described in the first aspect or any possible implementation of the first aspect.

[0016] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method as described in the first aspect or any possible implementation of the first aspect.

[0017] This application provides an intelligent fire extinguishing method, system, foam fire truck, and storage medium for a foam fire truck. It acquires fire scene information, including the ignition point, fire temperature distribution information, and a first distance (the distance between the fire hose and the ignition point). Based on this first distance, it determines the mixing ratio of the extinguishing medium in the foam fire truck, which is the ratio of foam to water. Based on the fire temperature distribution information, it determines the required volume of fire-fighting foam for extinguishing the fire. Based on the mixing ratio and the volume of fire-fighting foam, it drives the foam truck's proportional mixing system to produce fire-fighting foam. This application improves the accuracy of selecting the mixing ratio by determining the distance between the foam fire truck and the ignition point. Determining the required volume of fire-fighting foam based on fire temperature distribution information not only improves the accuracy of judging the required amount of medium during fire fighting and rescue but also saves resources, thereby increasing rescue speed and reducing economic losses. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1This is a flowchart illustrating the implementation of the intelligent fire extinguishing method for foam fire trucks provided in this application embodiment;

[0020] Figure 2 This is a schematic diagram showing the angle between the ladder and the horizontal ground provided in an embodiment of this application;

[0021] Figure 3 This is a schematic diagram of the arc between the fire hose and the ignition point provided in the embodiments of this application;

[0022] Figure 4 This is a schematic diagram of the structure of the intelligent fire extinguishing system for foam fire trucks provided in the embodiments of this application;

[0023] Figure 5 This is a schematic diagram of the foam fire truck provided in the embodiments of this application. Detailed Implementation

[0024] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0025] To make the objectives, technical solutions, and advantages of this application clearer, the following description will be provided in conjunction with the accompanying drawings and specific embodiments.

[0026] Figure 1 The implementation flowchart of the intelligent fire extinguishing method for foam fire trucks provided in the embodiments of this application is described in detail below:

[0027] In step 101, fire scene information is obtained, which includes the ignition point, fire temperature distribution information, and a first distance, which is the distance between the fire hose and the ignition point of the fire.

[0028] The first distance is the straight-line distance between the fire hose and the point of ignition.

[0029] In this embodiment of the application, an infrared camera device is used to acquire fire scene information images of the area where the fire occurred. The fire scene information includes the ignition point, fire temperature distribution information, and a first distance between the fire hose and the ignition point.

[0030] In one possible implementation, step 101 may include:

[0031] Acquire infrared images of the fire, including the geographical locations of various locations;

[0032] The infrared image is spatially divided to generate multiple sub-space images;

[0033] Each subspace image is input into the temperature prediction model, and the temperature information of each subspace image is output. The temperature information of each subspace image is combined to form fire temperature distribution information. The temperature prediction model is constructed based on YOLO.

[0034] The location of the subspace image corresponding to the maximum temperature is selected from the fire temperature distribution information as the ignition point of the fire.

[0035] The distance between the geographical location of the fire point and the geographical location of the fire hose is obtained using an infrared ranging sensor, and the distance between the fire point and the fire hose is taken as the first distance.

[0036] Optionally, infrared images of the fire area are acquired using an infrared camera device. These images include the geographical locations of various points within the fire area. The infrared images are then divided into multiple sub-spatial images, with the smallest possible spatial division. Each sub-spatial image is input into a temperature prediction model built based on the YOLO algorithm. The model outputs the temperature information corresponding to each sub-spatial image, and the temperature information from all sub-spatial images is integrated into fire temperature distribution information.

[0037] Then, the maximum temperature is selected from the fire temperature distribution information, and the geographical location of the subspace image where the maximum temperature is located is taken as the location of the current fire ignition point.

[0038] Finally, the straight-line distance between the location of the fire hose and the location of the fire point is obtained using an infrared ranging sensor, which is used as the first distance.

[0039] In one possible implementation, the process of constructing the temperature prediction model can be as follows:

[0040] Acquire historical infrared images and obtain the corresponding temperature information for those images;

[0041] Construct a YOLO model;

[0042] By using historical infrared images as input and the corresponding temperature information as output, a YOLO model is trained to obtain a temperature prediction model.

[0043] Optionally, the temperature prediction model is built based on the YOLO algorithm, and the specific construction process is as follows:

[0044] Historical infrared images of past fires are acquired, and temperature information at corresponding locations on these images is obtained. A YOLO model is constructed using the YOLO algorithm, with the historical infrared images serving as input and the corresponding temperature information as output. The YOLO model is then trained to obtain a temperature prediction model.

[0045] The embodiments of this application can shorten the time for acquiring temperature information by constructing and training a temperature prediction model, and can also improve the accuracy of the analysis between infrared images and temperature.

[0046] In step 102, the mixing ratio of the extinguishing medium of the foam fire truck is determined based on the first distance. The mixing ratio of the extinguishing medium is the mixing ratio of foam and water.

[0047] In this embodiment of the application, the mixing ratio of the extinguishing medium, which is a mixture of foam and water, in the foam fire truck is determined based on the first distance between the fire hose and the ignition point obtained in step 101.

[0048] In one possible implementation, the mixing ratio includes a first mixing ratio and a second mixing ratio.

[0049] Optionally, the mixing ratio of the fire-fighting foam includes a first mixing ratio and a second mixing ratio, wherein the first mixing ratio can be a 3% mixing ratio and the second mixing ratio can be 6%. For example, when the mixing ratio is 3%, 100 liters of fire-fighting foam includes 3 liters of foam and 97 liters of water.

[0050] In one possible implementation, step 102 may include:

[0051] Obtain the first preset spray velocity of the fire-fighting foam;

[0052] Based on the first distance and the first preset spray speed, determine the transmission time of the fire foam from the fire hose to the ignition point;

[0053] Determine if the transmission duration exceeds the first duration threshold;

[0054] If the transmission duration exceeds the first duration threshold, the mixing ratio of the foam fire truck extinguishing medium is determined to be the first mixing ratio.

[0055] If the transmission time is not greater than the first time threshold, the mixing ratio of the foam fire truck extinguishing medium is determined to be the second mixing ratio.

[0056] The first mixing ratio is less than the second mixing ratio.

[0057] The foam mixing ratio is also related to the duration of air contact; the longer the contact time, the smaller the mixing ratio.

[0058] Optionally, the pressure of the fire hose is set, i.e., the first preset spray velocity v of the fire hose spraying fire-fighting foam is determined. p1 For the first distance l1 and the first preset spray distance v p1 Calculate the ratio, i.e., t1 = l 1 / v p1 Determine the transmission time t1 of the fire-fighting foam from the fire hose to the ignition point.

[0059] After obtaining the transmission duration t1, determine whether the transmission duration t1 is greater than the first duration threshold t. y1 If the transmission duration t1 is greater than the first duration threshold t y1 That is, t1 > t y1 Then, the mixing ratio of the extinguishing medium in the foam fire truck is determined as the first mixing ratio. If the transmission duration t1 is not greater than the first duration threshold t... y1 That is, t1≤t y1 Therefore, the mixing ratio of the extinguishing medium in the foam fire truck is determined to be the second mixing ratio. The first mixing ratio is less than the second mixing ratio.

[0060] This application embodiment determines the time it takes for the fire foam to come into contact with air from the fire nozzle to the ignition point based on the first distance and the first preset spray speed of the fire foam sprayed by the fire hose, and determines the mixing ratio of the fire foam. This can improve the accuracy of the selection of the mixing ratio of the fire foam, provide a higher quality extinguishing medium for subsequent fire extinguishing, and thus improve the extinguishing rate and accuracy.

[0061] In step 103, the volume of fire-fighting foam required to extinguish the fire is determined based on the fire temperature distribution information.

[0062] In this embodiment of the application, the total volume of fire-fighting foam, the extinguishing medium required for extinguishing the current fire, is determined based on the fire temperature distribution information obtained in step 101.

[0063] In one possible implementation, step 103 may include:

[0064] Select the temperature value corresponding to the ignition point from the fire temperature distribution information;

[0065] The temperature value of the ignition point is input into the temperature-volume prediction model, and the fire-fighting foam volume corresponding to the ignition point temperature is output. The temperature-volume prediction model is constructed based on a generalized regression neural network.

[0066] Determine the ratio of the distribution area of ​​the fire points to the infrared image, and use this ratio as the first ratio;

[0067] The ratio of the fire-fighting foam volume corresponding to the ignition point temperature to the first ratio is calculated to obtain the fire-fighting foam volume required to extinguish the fire.

[0068] The temperature at the ignition point is generally the highest temperature at the entire fire scene.

[0069] Optionally, the ignition point area of ​​the fire is determined, and the temperature value corresponding to the ignition point is selected from the fire temperature distribution information. This temperature value is input into the temperature-volume prediction model to obtain the fire-fighting foam volume corresponding to the ignition point temperature. Then, the ratio of the distribution area of ​​the ignition point to the fire distribution area is calculated, and this ratio is used as the first ratio. The fire-fighting foam volume corresponding to the ignition point temperature and the first ratio are input into the first formula to obtain the fire-fighting foam volume required to extinguish the fire. The first formula is as follows:

[0070]

[0071] Where V0 is the volume of fire-fighting foam required to extinguish the fire, V1 is the volume of fire-fighting foam corresponding to the ignition point temperature, and α is the first ratio.

[0072] In one possible implementation, the temperature-volume prediction model is constructed as follows:

[0073] Obtain the historical temperature of the ignition point of a historical fire, as well as the volume of firefighting foam required to extinguish the ignition point;

[0074] Construct a generalized regression neural network model;

[0075] Using the historical temperature of the ignition point as input and the volume of fire-fighting foam required to extinguish the ignition point as output, a generalized regression neural network model is trained to obtain a temperature-volume prediction model.

[0076] This application embodiment determines the total volume of fire-fighting foam required to extinguish a fire by measuring the volume of fire-fighting foam needed to extinguish the fire at the ignition point temperature and the proportion of the ignition point distribution area in the overall fire distribution area. This not only provides sufficient extinguishing medium but also contributes to the efficiency and speed of fire extinguishing.

[0077] In step 104, fire foam is produced by the fire foam proportioning system of the foam fire truck, based on the mixing ratio and the volume of fire foam.

[0078] In this embodiment of the application, the fire-fighting foam mixing system of the foam fire truck is controlled to produce fire-fighting foam of a corresponding volume with a corresponding mixing ratio, based on the mixing ratio of the fire-fighting foam determined in step 102 and the volume of the fire-fighting foam determined in step 103, in order to extinguish the fire.

[0079] In one possible implementation, after step 101, the method may further include:

[0080] Determine the extension angle of the ladder of the foam fire truck based on the location of the fire and the location of the foam fire truck.

[0081] The extension length of the ladder is determined based on the extension angle and the first distance.

[0082] Calculate the difference between the first distance and the extension length as the distance between the ladder and the point of ignition;

[0083] Accordingly, root step 102 may include:

[0084] The mixing ratio of the extinguishing medium for the foam fire truck is determined based on the distance between the ladder and the fire point.

[0085] Optionally, the extension angle of the ladder of the foam fire truck is determined based on the location of the fire point and the location of the foam fire truck, with reference to... Figure 2 A represents the location of the fire truck, B represents the location of the fire, and θ represents the angle between the ladder of the foam fire truck and the horizontal plane, i.e., the extension angle of the ladder of the foam fire truck.

[0086] To ensure the safety of firefighters and equipment, the ladder should not extend too close to the fire. Therefore, based on the extension angle and initial distance, a preset percentage of the initial distance is selected as the extension length of the ladder. (Refer to...) Figure 2 The first distance is l1, and the extension length of the ladder is al1.

[0087] After determining the extension length al1 of the ladder, the difference between the first distance and the extension length is calculated as the straight-line distance between the ladder and the fire point. Using this straight-line distance and the second preset spray velocity of the fire-fighting foam, the mixing ratio of the extinguishing medium of the foam fire truck is determined.

[0088] In one possible implementation, determining the mixing ratio of the foam fire extinguishing medium based on the distance between the ladder and the fire point may include:

[0089] Obtain the second preset spray velocity of the fire-fighting foam;

[0090] The transmission time of fire-fighting foam from the fire hose to the ignition point is determined based on the distance between the ladder and the ignition point and the second preset spray speed.

[0091] Determine whether the transmission duration exceeds the second duration threshold;

[0092] If the transmission duration exceeds the second duration threshold, the mixing ratio of the foam fire truck extinguishing medium is determined to be the first mixing ratio.

[0093] If the transmission duration is not greater than the second duration threshold, then the mixing ratio of the foam fire truck extinguishing medium is determined to be the second mixing ratio;

[0094] The first mixing ratio is less than the second mixing ratio.

[0095] Optionally, the pressure of the fire hose is set, i.e., the second preset spray velocity v of the fire hose spraying fire-fighting foam is determined. p2 The distance l2 between the ladder and the ignition point and the second preset spray distance v. p2 Calculate the ratio, i.e., t2 = l2 / v p2 Determine the transmission time t2 of the fire-fighting foam from the fire hose to the ignition point.

[0096] After obtaining the transmission duration t2, determine whether the transmission duration t2 is greater than the second duration threshold t. y2 If the transmission duration t2 is greater than the second duration threshold t y2 That is, t2 > t y2 Then, the mixing ratio of the extinguishing medium in the foam fire truck is determined as the first mixing ratio. If the transmission duration t2 is not greater than the second duration threshold t... y2 That is, t2≤t y2 Therefore, the mixing ratio of the extinguishing medium in the foam fire truck is determined to be the second mixing ratio. The first mixing ratio is less than the second mixing ratio.

[0097] In one possible implementation, the acquired fire scene information may also include the radian distance between the fire hose and the ignition point, which can be referenced. Figure 3 The length of the arc distance is determined by the initial distance between the fire hose and the fire point, and the location of the fire hose and the fire point. The specific calculation process is as follows:

[0098] Reference Figure 3 Point A is the location of the fire hose, and point B is the location of the fire. Arc AB is used as the tangent line to points A and B respectively. A and l B With point A as the perpendicular point, draw a line perpendicular to the tangent line l. A A perpendicular line is drawn from point B to the tangent line l. B The perpendicular line from point O is given. AO and BO are the radii of arc AB. The length of arc AB is then calculated using the formula L = n × π × r / 180, where n is the central angle and r is the radius.

[0099] Calculating the mixing ratio of the extinguishing medium in the foam fire truck using the length of arc AB can improve the accuracy of the mixing ratio calculation, thereby improving the accuracy of the fire foam volume.

[0100] In one possible implementation, after the extension length of the ladder of the foam fire truck is determined according to a preset percentage of the first distance, the arc distance between the fire hose and the point of ignition is re-determined according to the above-mentioned arc length calculation method.

[0101] This application embodiment, through the calculation of two radian distances, can further improve the calculation of the mixing ratio of fire-fighting foam and the calculation of the volume of fire-fighting foam required to extinguish a fire.

[0102] This application provides an intelligent fire extinguishing method for foam fire trucks. The method involves acquiring fire scene information, including the ignition point, fire temperature distribution information, and a first distance (the distance between the fire hose and the ignition point). Based on this first distance, the mixing ratio of the extinguishing medium in the foam fire truck is determined, which is the ratio of foam to water. Based on the fire temperature distribution information, the required volume of fire-fighting foam for extinguishing the fire is determined. Based on the mixing ratio and the volume of fire-fighting foam, the fire-fighting foam proportional mixing system of the foam fire truck is activated to produce fire-fighting foam. This application improves the accuracy of selecting the mixing ratio by determining the distance between the foam fire truck and the ignition point. Determining the required volume of fire-fighting foam based on fire temperature distribution information not only improves the accuracy of judging the required amount of medium during fire fighting and rescue but also saves resources, thereby increasing rescue speed and reducing economic losses.

[0103] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0104] The following are device embodiments of this application. For details not described in detail, please refer to the corresponding method embodiments described above.

[0105] Figure 4 A schematic diagram of the intelligent fire extinguishing system for foam fire trucks provided in an embodiment of this application is shown. For ease of explanation, only the parts relevant to the embodiment of this application are shown, and are described in detail below:

[0106] like Figure 4 As shown, the foam fire truck intelligent fire extinguishing system 4 includes:

[0107] The acquisition module 41 is used to acquire fire scene information, which includes the ignition point, fire temperature distribution information, and a first distance, which is the distance between the fire hose and the ignition point of the fire.

[0108] The mixing ratio determination module 42 is used to determine the mixing ratio of the extinguishing medium of the foam fire truck based on the first distance. The mixing ratio of the extinguishing medium is the mixing ratio of foam and water.

[0109] The volume determination module 43 is used to determine the volume of fire-fighting foam required to extinguish the fire based on the fire temperature distribution information.

[0110] Drive module 44 is used to drive the fire foam proportioning system of the foam fire truck to produce fire foam according to the mixing ratio and the volume of fire foam.

[0111] This application provides an intelligent fire extinguishing system for foam fire trucks. By acquiring fire scene information, including the ignition point, fire temperature distribution information, and a first distance (the distance between the fire hose and the ignition point), the system determines the mixing ratio of the extinguishing agent (foam and water) based on this first distance. It also determines the required volume of fire-fighting foam needed to extinguish the fire based on the fire temperature distribution information. Finally, it drives the foam truck's foam mixing system to produce the required volume of fire-fighting foam based on the mixing ratio and the required volume of fire-fighting foam. This application improves the accuracy of selecting the mixing ratio by determining the distance between the foam fire truck and the fire point. Furthermore, determining the required volume of fire-fighting foam based on fire temperature distribution information not only improves the accuracy of judging the required amount of agent during fire fighting and rescue but also saves resources, thereby increasing rescue speed and reducing economic losses.

[0112] In one possible implementation, the acquisition module can be used for:

[0113] Acquire infrared images of the fire, including the geographical locations of various locations;

[0114] The infrared image is spatially divided to generate multiple sub-space images;

[0115] Each subspace image is input into the temperature prediction model, and the temperature information of each subspace image is output. The temperature information of each subspace image is combined to form fire temperature distribution information. The temperature prediction model is constructed based on the YOLO algorithm.

[0116] The location of the subspace image corresponding to the maximum temperature is selected from the fire temperature distribution information as the ignition point of the fire.

[0117] The distance between the geographical location of the fire point and the geographical location of the fire hose is obtained using an infrared ranging sensor, and the distance between the fire point and the fire hose is taken as the first distance.

[0118] In one possible implementation, the process of constructing the temperature prediction model can be as follows:

[0119] Acquire historical infrared images and obtain the corresponding temperature information for those images;

[0120] Construct a YOLO model;

[0121] By using historical infrared images as input and the corresponding temperature information as output, a YOLO model is trained to obtain a temperature prediction model.

[0122] In one possible implementation, the mixing ratio may include a first mixing ratio and a second mixing ratio; the mixing ratio determination module may be used for:

[0123] Obtain the first preset spray velocity of the fire-fighting foam;

[0124] Based on the first distance and the first preset spray speed, determine the transmission time of the fire foam from the fire hose to the ignition point;

[0125] Determine if the transmission duration exceeds the first duration threshold;

[0126] If the transmission duration exceeds the first duration threshold, the mixing ratio of the foam fire truck extinguishing medium is determined to be the first mixing ratio.

[0127] If the transmission time is not greater than the first time threshold, the mixing ratio of the foam fire truck extinguishing medium is determined to be the second mixing ratio.

[0128] The first mixing ratio is less than the second mixing ratio.

[0129] In one possible implementation, the volume determination module can be used to:

[0130] Select the temperature value corresponding to the ignition point from the fire temperature distribution information;

[0131] The temperature value of the ignition point is input into the temperature-volume prediction model, and the fire-fighting foam volume corresponding to the ignition point temperature is output. The temperature-volume prediction model is constructed based on a generalized regression neural network.

[0132] Determine the ratio of the distribution area of ​​the fire points to the infrared image, and use this ratio as the first ratio;

[0133] The ratio of the fire-fighting foam volume corresponding to the ignition point temperature to the first ratio is calculated to obtain the fire-fighting foam volume required to extinguish the fire.

[0134] In one possible implementation, the system also includes an extension length calculation module, which can be used for:

[0135] Determine the extension angle of the ladder of the foam fire truck based on the location of the fire and the location of the foam fire truck.

[0136] The extension length of the ladder is determined based on the extension angle and the first distance.

[0137] Calculate the difference between the first distance and the extension length as the distance between the ladder and the point of ignition;

[0138] Accordingly, the mixing ratio determination module can be used for:

[0139] The mixing ratio of the extinguishing medium for the foam fire truck is determined based on the distance between the ladder and the fire point.

[0140] In one possible implementation, the mixing ratio may include a first mixing ratio and a second mixing ratio; the mixing ratio determining module may also be used to include:

[0141] Obtain the second preset spray velocity of the fire-fighting foam;

[0142] The transmission time of fire-fighting foam from the fire hose to the ignition point is determined based on the distance between the ladder and the ignition point and the second preset spray speed.

[0143] Determine whether the transmission duration exceeds the second duration threshold;

[0144] If the transmission duration exceeds the second duration threshold, the mixing ratio of the foam fire truck extinguishing medium is determined to be the first mixing ratio.

[0145] If the transmission duration is not greater than the second duration threshold, then the mixing ratio of the foam fire truck extinguishing medium is determined to be the second mixing ratio;

[0146] The first mixing ratio is less than the second mixing ratio.

[0147] Figure 5 This is a schematic diagram of the foam fire truck provided in an embodiment of this application. Figure 5 As shown, the foam fire truck 5 in this embodiment includes: a processor 50, a memory 51, and a computer program 52 stored in the memory 51 and executable on the processor 50. When the processor 50 executes the computer program 52, it implements the steps in the various embodiments of the intelligent fire extinguishing method for foam fire trucks described above, for example... Figure 1 Steps 101 to 104 are shown. Alternatively, when the processor 50 executes the computer program 52, it implements the functions of each module in the above-described device embodiments, for example... Figure 4 The functions of each module are shown.

[0148] For example, the computer program 52 can be divided into one or more modules, which are stored in the memory 51 and executed by the processor 50 to complete this application. The one or more modules / units can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 52 in the foam fire truck 5. For example, the computer program 52 can be divided into... Figure 4 The modules shown.

[0149] The foam fire truck 5 can be a computing device such as a desktop computer, laptop, handheld computer, or cloud server. The foam fire truck 5 may include, but is not limited to, a processor 50 and a memory 51. Those skilled in the art will understand that... Figure 5 This is merely an example of foam fire truck 5 and does not constitute a limitation on foam fire truck 5. It may include more or fewer components than shown, or combine certain components, or different components. For example, the foam fire truck may also include input / output devices, network access devices, buses, etc.

[0150] The processor 50 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0151] The memory 51 can be an internal storage unit of the foam fire truck 5, such as a hard drive or memory. The memory 51 can also be an external storage device of the foam fire truck 5, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD card, Flash Card), etc. Furthermore, the memory 51 can include both internal and external storage units of the foam fire truck 5. The memory 51 is used to store the computer program and other programs and data required by the foam fire truck. The memory 51 can also be used to temporarily store data that has been output or will be output.

[0152] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0153] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0154] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0155] In the embodiments provided in this application, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling or direct coupling or communication connection may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0156] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0157] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0158] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above-described embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various embodiments of the intelligent fire extinguishing method for foam fire trucks described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately added to or subtracted from the content as required by the legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium may not include electrical carrier signals and telecommunication signals.

[0159] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A smart fire extinguishing method for foam fire trucks, characterized in that, include: Acquire fire scene information, which includes the ignition point, fire temperature distribution information, and a first distance, wherein the first distance is the distance between the fire hose and the ignition point of the fire. Based on the first distance, the mixing ratio of the extinguishing medium of the foam fire truck is determined, wherein the mixing ratio of the extinguishing medium is the mixing ratio of foam and water; Based on the fire temperature distribution information, determine the volume of fire-fighting foam required to extinguish the fire; The fire-fighting foam is produced by the fire-fighting foam proportioning system driving the foam fire truck according to the mixing ratio and the volume of the fire-fighting foam: The fire scene information also includes the arc distance between the fire hose and the ignition point. Determining the mixing ratio of the foam fire truck extinguishing medium based on the first distance includes: The length of the arc distance is determined based on the first distance and the ignition point of the fire; Calculate the mixing ratio of the extinguishing medium of the foam fire truck based on the length of the arc distance; The mixing ratio includes a first mixing ratio and a second mixing ratio; determining the mixing ratio of the foam fire truck extinguishing medium based on the first distance includes: Obtain the first preset spray velocity of the fire-fighting foam; Based on the first distance and the first preset spray speed, determine the transmission time of the fire-fighting foam from the fire hose to the ignition point; Determine whether the transmission duration is greater than a first duration threshold; If the transmission duration is greater than the first duration threshold, then the mixing ratio of the foam fire truck extinguishing medium is determined to be the first mixing ratio; If the transmission duration is not greater than the first duration threshold, then the mixing ratio of the foam fire truck extinguishing medium is determined to be the second mixing ratio; The first mixing ratio is less than the second mixing ratio.

2. The intelligent fire extinguishing method for foam fire trucks according to claim 1, characterized in that, The acquisition of fire scene information includes: Acquire infrared images of the fire, including the geographical locations of each location; The infrared image is spatially divided to generate multiple sub-space images; Each subspace image is input into the temperature prediction model, and the temperature information of each subspace image is output. The temperature information of each subspace image is then combined to form the fire temperature distribution information. The temperature prediction model is constructed based on the YOLO algorithm. The location of the subspace image corresponding to the maximum temperature is selected from the fire temperature distribution information as the ignition point of the fire. The distance between the geographical location of the fire point and the geographical location of the fire hose is obtained using an infrared ranging sensor, and the distance between the fire point and the fire hose is taken as the first distance.

3. The intelligent fire extinguishing method for foam fire trucks according to claim 2, characterized in that, The construction process of the temperature prediction model is as follows: Acquire historical infrared images and obtain the temperature information corresponding to the historical infrared images; Construct a YOLO model; The historical infrared image is used as input, and the temperature information corresponding to the historical infrared image is used as output to train the YOLO model, thereby obtaining the temperature prediction model.

4. The intelligent fire extinguishing method for foam fire trucks according to claim 2, characterized in that, Determining the volume of fire-fighting foam required to extinguish the fire based on the fire temperature distribution information includes: Select the temperature value corresponding to the ignition point from the fire temperature distribution information; The temperature value of the ignition point is input into the temperature-volume prediction model, and the fire-fighting foam volume corresponding to the ignition point temperature is output. The temperature-volume prediction model is constructed based on a generalized regression neural network. Determine the ratio of the distribution area of ​​the ignition point to the infrared image, and use the ratio as the first ratio; The ratio of the fire-fighting foam volume corresponding to the ignition point temperature to the first ratio is calculated to obtain the fire-fighting foam volume required to extinguish the fire.

5. The intelligent fire extinguishing method for foam fire trucks according to claim 1, characterized in that, After acquiring the fire scene information, the method further includes: Based on the location of the fire and the location of the foam fire truck, determine the extension angle of the ladder of the foam fire truck; Based on the extension angle and the first distance, the extension length of the ladder is determined; Calculate the difference between the first distance and the extension length, and use it as the distance between the ladder and the ignition point; Accordingly, determining the mixing ratio of the foam fire truck extinguishing medium based on the first distance includes: The mixing ratio of the extinguishing medium of the foam fire truck is determined based on the distance between the ladder and the ignition point.

6. The intelligent fire extinguishing method for foam fire trucks according to claim 5, characterized in that, The mixing ratio includes a first mixing ratio and a second mixing ratio, wherein the first mixing ratio is smaller than the second mixing ratio; determining the mixing ratio of the foam fire truck extinguishing medium based on the distance between the ladder and the fire point includes: Obtain the second preset spray velocity of the fire-fighting foam; The duration of the fire-fighting foam from the fire hose to the fire point is determined based on the distance between the ladder and the ignition point and the second preset spray speed. Determine whether the duration is greater than the second duration threshold; If the duration is greater than the second duration threshold, then the mixing ratio of the foam fire truck extinguishing medium is determined to be the first mixing ratio; If the duration is not greater than the second duration threshold, then the mixing ratio of the foam fire truck extinguishing medium is determined to be the second mixing ratio.

7. An intelligent fire extinguishing system for foam fire trucks, characterized in that, include: The acquisition module is used to acquire fire scene information, which includes the ignition point, fire temperature distribution information, and a first distance, wherein the first distance is the distance between the fire hose and the ignition point of the fire. A mixing ratio determination module is used to determine the mixing ratio of the extinguishing medium of the foam fire truck based on the first distance, wherein the mixing ratio of the extinguishing medium is the mixing ratio of foam and water; The volume determination module is used to determine the volume of fire-fighting foam required to extinguish the fire based on the fire temperature distribution information. A drive module is used to drive the fire-fighting foam proportioning system of the foam fire truck to produce the fire-fighting foam according to the mixing ratio and the volume of the fire-fighting foam. The fire scene information also includes the arc distance between the fire hose and the ignition point, and the mixing ratio determination module is used for: The length of the arc distance is determined based on the first distance and the ignition point of the fire; Calculate the mixing ratio of the extinguishing medium of the foam fire truck based on the length of the arc distance; The mixing ratio includes a first mixing ratio and a second mixing ratio; the mixing ratio determination module is specifically used for: Obtain the first preset spray velocity of the fire-fighting foam; Based on the first distance and the first preset spray speed, determine the transmission time of the fire-fighting foam from the fire hose to the ignition point; Determine whether the transmission duration is greater than a first duration threshold; If the transmission duration is greater than the first duration threshold, then the mixing ratio of the foam fire truck extinguishing medium is determined to be the first mixing ratio; If the transmission duration is not greater than the first duration threshold, then the mixing ratio of the foam fire truck extinguishing medium is determined to be the second mixing ratio; The first mixing ratio is less than the second mixing ratio.

8. A foam fire truck, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the intelligent fire extinguishing method for foam fire trucks as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the intelligent fire extinguishing method for foam fire trucks as described in any one of claims 1 to 6.

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